Data Science Version Control or DVC is an open-source tool for data science and
machine learning projects. With a simple and flexible Git-like architecture and
interface it helps data scientists:
* manage machine learning models - versioning, including data sets and
transformations (scripts) that were used to generate models;
* make projects reproducible;
* make projects shareable;
* manage experiments with branching and metrics tracking.
It aims to replace tools like Excel and Docs that are being commonly used as a
knowledge repo and a ledger for the team, ad-hoc scripts to track and move
deploy different model versions, ad-hoc data file suffixes and prefixes.
WWW: https://dvc.org/

Bump PORTREVISION for ports depending on the canonical version of GCC
as defined in Mk/bsd.default-versions.mk which has moved from GCC 8.3
to GCC 9.1 under most circumstances now after revision 507371.
This includes ports
- with USE_GCC=yes or USE_GCC=any,
- with USES=fortran,
- using Mk/bsd.octave.mk which in turn features USES=fortran, and
- with USES=compiler specifying openmp, nestedfct, c11, c++0x, c++11-lang,
c++11-lib, c++14-lang, c++17-lang, or gcc-c++11-lib
plus, everything INDEX-11 shows with a dependency on lang/gcc9 now.
PR: 238330